期刊
COMMUNICATIONS EARTH & ENVIRONMENT
卷 3, 期 1, 页码 -出版社
SPRINGERNATURE
DOI: 10.1038/s43247-022-00564-w
关键词
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资金
- Harvard University Center for the Environment Postdoctoral Fellowship program
- United Nations Development Programme
- Avatar Alliance Foundation
- Margaret A. Cargill Foundation
- David and Lucile Packard Foundation
- Gordon and Betty Moore Foundation
- Grantham Foundation for the Protection of the Environment
- W. M. Keck Foundation
- John D. and Catherine T. MacArthur Foundation
- Andrew Mellon Foundation
- Arizona State University
- British Ecological Society
- ERC [291585]
- HSBC Malaysia
- University of Zurich
- European Research Council (ERC) [291585] Funding Source: European Research Council (ERC)
This study highlights the importance of forest type in understanding the response of tropical forests to environmental change. By analyzing high-resolution airborne remotely sensed data, the researchers identified and mapped seven forest types in Malaysian Borneo. They found ecologically relevant variations in forest type, which had significant impacts on carbon stock, growth, and mortality rate. Leaf mass per area and canopy phosphorus were identified as critical traits for distinguishing forest types. The findings emphasize the significance of these parameters for accurately mapping tropical forest types using satellite observations.
Although tropical forests differ substantially in form and function, they are often represented as a single biome in global change models, hindering understanding of how different tropical forests will respond to environmental change. The response of the tropical forest biome to environmental change is strongly influenced by forest type. Forest types differ based on functional traits and forest structure, which are readily derived from high resolution airborne remotely sensed data. Whether the spatial resolution of emerging satellite-derived hyperspectral data is sufficient to identify different tropical forest types is unclear. Here, we resample airborne remotely sensed forest data at spatial resolutions relevant to satellite remote sensing (30 m) across two sites in Malaysian Borneo. Using principal component and cluster analysis, we derive and map seven forest types. We find ecologically relevant variations in forest type that correspond to substantial differences in carbon stock, growth, and mortality rate. We find leaf mass per area and canopy phosphorus are critical traits for distinguishing forest type. Our findings highlight the importance of these parameters for accurately mapping tropical forest types using space borne observations. Functional variations in tropical forests can be determined from remotely sensed forest trait and structural attributes at spatial resolutions relevant to satellite-based observations, according to a coarse resolution analysis of airborne remotely sensed data in Malaysian Borneo.
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